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Bipolar magnetic regions (BMRs) provide crucial information about solar magnetism. They exhibit varying morphology and magnetic properties throughout their lifetime, and studying these properties can provide valuable insights into the workings of the solar dynamo. The majority of previous studies have counted every detected BMR as a new one and have not been able to study the full life history of each BMR. To address this issue, we have developed Automatic Tracking Algorithm for BMRs (AutoTAB) that tracks the BMRs for their entire lifetime or throughout their disk passage. AutoTAB uses the binary maps of detected BMRs and their overlapping criterion to automatically track the regions. In this first article of this project, we provide a detailed description of the working of the algorithm and evaluate its strengths and weaknesses by comparing it with existing algorithms. AutoTAB excels in tracking even for the small BMRs (with a flux of ∼1020 Mx), and it has successfully tracked 9152 BMRs over the last two solar cycles (1996–2020), providing a comprehensive data set that depicts the evolution of various properties for each BMR. The tracked BMRs exhibit the well-known butterfly diagram and 11 yr solar cycle variation, except for small BMRs, which appear at all phases of the solar cycle and show a weak latitudinal dependence. Finally, we discuss the possibility of adapting our algorithm to other data sets and expanding the technique to track other solar features in the future.

We explore what fraction of delta sunspots with a sharp polarity inversion line (PIL) in photospheric magnetograms are produced by a writhe kink in an emerging twisted flux rope. Using simultaneous full-disk magnetograms and continuum images from the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory, we identified 28 random sharp-PIL delta sunspots that form well on the disk. Only one of these formed from a single newly emerged bipolar magnetic region (BMR) and is therefore a candidate for being produced by a single emerging writhe-kinked flux rope. This outcome indicates that few, if any, sharp-PIL delta sunspots are produced by a single emerging writhe-kinked flux rope; this is the main new finding of this paper. The remaining 27 are produced by the merging of two or more emerging or emerged BMRs. We refer to delta-sunspot genesis from a single BMR as Type I genesis. Among the other 27 delta sunspots, we identify three additional genesis types: Type II, Type III, and Type IV. For each of the four genesis types we present an observed example and schematic drawings depicting our proposed formation scenario(s). The core idea of these scenarios is that delta sunspots form when opposite-polarity magnetic flux is packed together by advection into a convective downflow.

Bipolar magnetic regions (BMRs) that appear on the solar photosphere are surface manifestations of the Sun’s internal magnetic field. With modern observations and continuous data streams, the study of BMRs has moved from manual sunspot catalogs to automated detection and tracking methods. In this work, we present an additional module to the existing BMR tracking algorithm, the Automatic Tracking Algorithm for Bipolar Magnetic Regions (AutoTAB), which focuses on identifying emerging signatures of BMRs. Specifically, for regions newly detected on the solar disk, this module backtracks the BMRs to their point of emergence. From a total of about 12,000 BMRs identified by AutoTAB, we successfully backtracked 3080 cases. Within this backtracked sample, we find two distinct populations. One group shows the expected behavior of emerging regions, in which the magnetic flux increases significantly during the emerging phase. The other group consists of BMRs whose flux, however, does not exhibit substantial growth during their evolution, the instances where our algorithm fails to capture the initial emergence of the BMRs. We classify these as “discarded” BMRs and examine their statistical properties separately. Our analysis shows that these discarded BMRs do not display any preferred tilt angle distribution and do not show systematic latitudinal tilt dependence, in contrast to the trends typically associated with emerging BMRs. This indicates that including such regions in statistical studies of BMR properties can distort or mask the underlying physical characteristics. We therefore emphasise the importance of excluding the discarded population from the whole dataset when analysing the statistical behavior of BMRs.

We study the latitudinal distribution and evolution of sunspot areas of Solar Cycles 12 – 23 (SC12–23) and sunspot groups of Solar Cycles 8 – 23 (SC8–23) for even and odd cycles. The Rician distribution is the best-fit function for both even and odd sunspots group latitudinal occurrence. The mean and variance for even northern/southern butterfly wing sunspots are 14.94/14.76 and 58.62/56.08, respectively, and the mean and variance for odd northern/southern wing sunspots are 15.52/15.58 and 61.77/58.00, respectively. Sunspot groups of even cycle wings are thus at somewhat lower latitudes on average than sunspot groups of the odd cycle wings, i.e. about 0.6 degrees for northern hemisphere wings and 0.8 degrees for southern hemisphere wings. The spatial analysis of sunspot areas between SC12–23 shows that the small sunspots are at lower solar latitudes of the Sun than the large sunspots for both odd and even cycles, and also for both hemispheres. Temporal evolution of sunspot areas shows a lack of large sunspots after four years (exactly between 4.2 – 4.5 years), i.e. about 40% after the start of the cycle, especially for even cycles. This is related to the Gnevyshev gap and is occurring at the time when the evolution of the average sunspot latitudes crosses about 15 degrees. The gap is, however, clearer for even cycles than odd ones. Gnevyshev gap divides the cycle into two disparate parts: the ascending phase/cycle maximum and the declining phase of the sunspot cycle.

Bipolar sunspots, or more generally, bipolar magnetic regions (BMRs), are the dynamic magnetic regions that appear on the solar surface and are central to solar activity. One striking feature of these regions is that they are often tilted with respect to the equator, and this tilt increases with the latitude of appearance, popularly known as Joy’s law. Although this law has been examined for over a century through various observations, its physical origin is still not established. An attractive theory that has been put forward behind Joy’s law is the Coriolis force acting on the rising flux tube in the convection zone, which has been studied using the thin flux tube model. However, observational support for this theory is limited. If the Coriolis force is the cause of the tilt, then we expect BMRs to hold to Joy’s law at their initial emergence on the surface. By automatically identifying the BMRs over the last two solar cycles from high-resolution magnetic observations, we robustly capture their initial emergence signatures on the surface. We find that from their appearance, BMRs exhibit tilts consistent with Joy’s law. This early tilt signature of BMRs suggests that the tilt is developed underneath the photosphere, driven by the Coriolis force and helical convection, as predicted by the thin flux tube model. Considerable scatter around Joy’s law observed during the emergence phase, which reduces in the postemergence phase, reflects the interaction of the vigorous turbulent convection with the rising flux tubes in the near-surface layer.

The daily number of sunspot groups on the solar disk, as recorded by the programme of sunspot observations performed under the aegis of the Royal Observatory, Greenwich, UK, and subsequently the Royal Greenwich Observatory (RGO), is re-examined for the interval 1874 – 1885. The motivation for this re-examination is the key role that the RGO number of sunspot groups plays in the calculation of Group Sunspot Numbers (Hoyt and Schatten in Solar Phys. 179 , 189, 1998a ; Solar Phys. 181 , 491, 1998b ). A new dataset has been derived for the RGO daily number of sunspot groups in the interval 1874 – 1885. This new dataset attempts to achieve complete consistency between the sunspot data presented in the three main sections of the RGO publications and also incorporates all known errata and additions. It is argued that days for which no RGO solar photograph was acquired originally should be regarded, without exception, as being days without meaningful sunspot data. The daily number of sunspot groups that Hoyt and Schatten assign to days without RGO photographs is frequently just a lower limit. Moreover, in the absence of a solar photograph, the daily number of sunspot groups is inevitably uncertain because of the known frequent occurrence of sunspot groups that exist for just a single day. The elimination of days without photographs changes the list of inter-comparison days on which both the primary RGO observer and a specified secondary comparison observer saw at least one sunspot group. The resulting changes in the personal correction factors of secondary observers then change the personal correction factors of overlapping tertiary observers, etc . In this way, numerical changes in the personal correction factors of secondary observers propagate away from the interval 1874 – 1885, thereby potentially changing the arithmetical calculation of Group Sunspot Numbers over an appreciably wider time interval.

The relative sunspot number is one of the major parameters for the study of long-term solar activity. The automatic calculation of the relative sunspot number is more stable and accurate as compared to manual methods. In this paper, we propose an algorithm that can detect sunspots, and divide them into groups to automatically calculate the relative sunspot number. Mathematical morphology was adopted to detect sunspots then group them. The data set used were the continuum images from SDO/HMI. The process was carried out on the overall HMI data available on the timespan from 2022 January to 2023 May with a time cadence of one day. The experimental results indicated that the method achieved high accuracy of 85.3%. It was well fitted with the international relative sunspot number provided by Solar Influences Data Analysis Center (CC = 0.91). We calculated the conversion factor K value of SDO/HMI for calculating the relative sunspots number (K = 1.03).

Solar activity generally exhibits cyclic behavior in terms of sunspot group number and sunspot positions every ≈11 yr. These sunspot data have therefore played key roles in numerous analyses of solar–terrestrial physics. However, their reconstructions prior to the 1830s have remained controversial and included significant data gaps, especially from the 1720s to the 1740s. Therefore, this study reviewed contemporary sunspot observations for 1727–1748 to add several forgotten records by Van Coesfelt in 1728–1729, Dûclos in 1736, Martin in 1737, and Cassini and Maraldi in 1748. On the basis of these records, this study revised the sunspot group number and newly derived the sunspot positions in this interval. The results show clearer solar cycles in sunspot group number than those of previous studies and indicate regular solar cycles with limited hemispheric asymmetry over Solar Cycles 0 to −2. The sunspot positions also show sunspot groups mostly at heliographic latitude φ fulfilling ∣φ∣ < 35° in both solar hemispheres, with slight equatorward motions. Furthermore, the solar minima between Solar Cycles −2 and −1 and between Solar Cycles −1 and 0 have been located around 1733.5 ± 0.5 and 1743 ± 0.5, indicating cycle lengths of 11.7 ± 0.5 yr and 10.0 ± 1.0 yr, respectively. Our results provide a chronological missing link between the Maunder Minimum and the regular solar cycles observed since Staudach’s observations from 1749 onward. This lets us better understand the transition of solar activity from the grand minimum to the regular solar cycles.

Sunspots are the most important indicator of the magnetic activity on the solar surface during a cycle. Every sunspot group is formed and shaped by the magnetic field of the Sun. Hence, the magnetic field intensity shows itself as the size of a sunspot group area on the surface. This shows that getting the development or evolution of sunspot groups over time means getting the change of magnetic field intensity during same interval. Here, to reveal the evolution of sunspot groups in a cycle, a method called Solar Cycle Analyzer Tool (SCAT) is presented. This method was developed as a part of Computer-Aided Measurements for Sunspots (CAMS) because the same subroutines and subprograms were used for calculations (Çakmak in Exp. Astron. 38:77–89, 2014). The developed software tracks sunspot groups every day and gives them the same group number. The confirmation is made by the user to prevent counting re-formations as a continuation of an old group in the same active region. With this method, the evolution of every sunspot group can be listed for each cycle year besides other cycle features like the daily and monthly sunspot relative numbers and distribution frequency of the sunspot group types. Since 2015, SCAT is being used to get data for the annual reports of Istanbul University Observatory.

An analysis of the photometric growth and decay rates of sunspots and pores was carried out. According to the Solar Dynamics Observatory/Helioseismic and Magnetic Imager data for the period 2010 May–2025 March, ≈3.5 × 105 sunspots and pores were detected and their evolution tracked. The growth and decay rates of sunspots depend nonmonotonically on the area. For small-area sunspots S ≲ 50 μsh, a rapid increase in velocity is observed with increasing area for the growth stage dSspgr≈0.2·S1.35 and for the decay stage dSspdc≈0.28·S1.26 μsh day−1. For sunspots S ≳ 50 μsh, the growth rate depends weakly on the area: dSspgr≈11.9·S0.32 μsh day−1. For the decay stage of sunspots with an area of S ≈ 50–150 μsh, the decay rate also depends weakly on the area and can be approximated as dSspdc≈11·S0.15 . For sunspot areas S ≳ 150 μsh, the decay rate accelerates with increasing area: dSspdc≈0.14·S0.96 μsh day−1. For solar pores, the growth and decay rates of solar pores are linearly related to the area. The growth and decay rates for the spots of the leading and trailing polarities are determined. In the range of spot areas S ≈ 100–200 μsh, the growth and decay rates of sunspots of trailing polarity are higher than those of sunspots of leading polarity.